Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-24T16:48:42.529Z Has data issue: false hasContentIssue false

Correlation between newborn size and gross fetal movement as counted by a fetal movement acceleration measurement recorder

Published online by Cambridge University Press:  14 July 2020

Keita Yatsuki
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
Eiji Ryo*
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
Masayoshi Morita
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
Michiharu Seto
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
Hideo Kamata
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
Yuriko Yonaga
Affiliation:
Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, Tokyo173-8606, Japan
*
Address for correspondence: Eiji Ryo, Department of Obstetrics and Gynecology, School of Medicine, Teikyo University, 2-11-1, Kaga, Itabashi-ku, Tokyo173-8606, Japan. Email: yonchi@med.teikyo-u.ac.jp

Abstract

The development of the fetal movement acceleration measurement (FMAM) recorder has enabled the accurate counting of gross fetal movements. The aim of the study was to investigate whether gross fetal movement is related to a newborn’s size. A total of 90 pregnant women who delivered singleton infant at term were recruited. Gross fetal movements were counted using an FMAM recorder during maternal sleep. The ratio of movement positive 10-s epochs to all epochs during one night was calculated as an index of fetal movement. Independent explanatory variables for the fetal movement index were selected from eight possibilities, that is, maternal age, gestational week, and the six physical measures of the newborn (height, weight, head circumference, chest circumference, Kaup index, and the ratio of head to chest circumference) with the stepwise regression procedure. The selected physical variables and the fetal movement index were analyzed using multiple regression analysis. A total of 2812.95 h from 423 night records were available. Gestational weeks and weight of the newborn were selected as the significant independent variables. Multiple regression analysis revealed that newborn weight had a positive correlation with the fetal movement index (p < 0.0001). The multiple regression equation was “The fetal movement index (%) = 34.9989−0.9088 × gestational weeks + 0.0033 × newborn weight (g).” A person’s physical ability and lifetime activity level may originate from fetal health. This study may provide a new way of looking at the Developmental Origins of Health and Disease theory.

Type
Original Article
Copyright
© The Author(s), 2020. Published by Cambridge University Press in association with the International Society for Developmental Origins of Health and Disease

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ryo, E, Nishihara, K, Matsumoto, S, Kamata, H. A new method for long-term home monitoring of fetal movement by pregnant women themselves. Med Eng Phys. 2012; 34, 566572.CrossRefGoogle ScholarPubMed
Ryo, E, Kamata, H, Seto, M. Decreased fetal movements at home were recorded by a newly developed fetal movement recorder in a case of a non-reassuring fetal status. J Metern Fetal Meonat Med. 2014; 27, 16041606.Google Scholar
Ryo, E, Kamata, H, Seto, M, Morita, M, Yatsuki, K. Correlation between umbilical cord length and gross fetal movement as counted by a fetal movement acceleration measurement recorder. Eur J Obstet Gynecol Repro Biol X. 2019; 1, 100003.Google ScholarPubMed
Ryo, E, Kamata, H, Seto, M, et al. Reference values for a fetal movement acceleration measurement recorder to count fetal movements. Pediatr Res. 2018; 83, 961968.CrossRefGoogle ScholarPubMed
Morita, M, Ryo, E, Kamata, H, Seto, M, Yatsuki, K. Counting fetal movements for small-gestational infants using a fetal movement acceleration measurement recorder. J Matern Fetal Neonat Med. 2019; 5, 17.Google Scholar
Nishihara, K, Ohki, N, Kamata, H, Ryo, E, Horiuchi, S. Automated software analysis of fetal movement recorded during a pregnant woman’s sleep at home. PLoS One. 2015; 10, e0130503.CrossRefGoogle ScholarPubMed
Kamata, H, Ryo, E, Seto, M, Morita, M, Nagaya, Y. Counting fetal hiccups using a fetal movement acceleration measurement recorder. J Matern Fetal Neonat Med. 2017; 30, 475478.CrossRefGoogle ScholarPubMed
Huang, C, Han, W, Fan, Y. Correlations study between increased fetal movement during the third trimester and neonatal outcome. BMC Preg Child. 2019; 19, 467.CrossRefGoogle Scholar
Tomoda, S, Brace, RA, Longo, LD. Amniotic fluid volume and fetal swallowing rate in sheep. Am J Physiol. 1985; 249, R133R138.Google Scholar
Fuchs, F, Aouinti, S, Souaied, M, et al. Association between amniotic fluid evaluation and fetal biometry: a prospective French Flash study. Sci Rep. 2018; 8, 7093.CrossRefGoogle ScholarPubMed
Moura-Dos-Santos, MA, Almeida, MB, Manhães-De-Castro, R, Katzmarzyk, P, Maia, JAR, Leandro, CG. Birth weight, body composition, and motor performance in 7- to 10-year-old children. Dev Med Child Neurol. 2015; 57, 470475.CrossRefGoogle ScholarPubMed
Dodds, R, Denison, HJ, Ntani, G, Cooper, C, Sayer, AA, Baird, J. Birth weight and muscle strength: a systematic review and meta-analysis. J Nutr Health Aging. 2012; 16, 609615.CrossRefGoogle ScholarPubMed
Lubans, DR, Morgan, PJ, Cliff, DP, Barnett, LM, Okely, AD. Fundamental movement skills in children and adolescents: review of associated health benefits. Sports Med. 2010; 40, 10191035.CrossRefGoogle ScholarPubMed
Tammelin, T, Näyhä, S, Hills, AP, Järvelin, MR. Adolescent participation in sports and adult physical activity. Am J Prev Med. 2003; 24, 2228.CrossRefGoogle ScholarPubMed
Telema, R. Tracking of physical activity from childhood to adulthood: a review. Obes Facts. 2009; 2, 187195.CrossRefGoogle Scholar
Hsu, CN, Tain, YL. The good, the bad, and the ugly of pregnancy nutrients and developmental programming of adult disease. Nutrients. 2019; 11(4), Pii: E894. doi: 10.3390/nu11040894.CrossRefGoogle ScholarPubMed
Lai, J, Nowlan, NC, Vaidyanathan, R, Shaw, CJ, Lees, CC. Fetal movement as a predictor of health. Acta Obstet Gynecol Scand. 2016; 95, 968975.CrossRefGoogle ScholarPubMed